On the Recognition of Printed Characters of Any Font and Size
IEEE Transactions on Pattern Analysis and Machine Intelligence
Prototype Extraction and Adaptive OCR
IEEE Transactions on Pattern Analysis and Machine Intelligence
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active learning using adaptive resampling
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Expectation Maximization for Weakly Labeled Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A hierarchical, HMM-based automatic evaluation of OCR accuracy for a digital library of books
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
A semi-automatic adaptive OCR for digital libraries
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
Digitizing a million books: challenges for document analysis
DAS'06 Proceedings of the 7th international conference on Document Analysis Systems
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This paper presents an architecture that enables the recognizer to learn incrementally and, thereby adapt to document image collections for performance improvement. We argue that the recognition scheme for a book could be considerably different from that designed for isolated pages. We employ learning procedures to capture the relevant information available online, and feed it back to update the knowledge of the system. Experimental results show the effectiveness of our design for improving the performance on-the-fly.